Stability of a class of complex-valued BAM neural networks with proportional delays and impulse via fixed point theory

Abstract

This paper mainly studies the stability of a class of proportional delay complex-valued BAM neural networks. Using the Banach fixed-point theorem, we obtain that the equilibrium points of the neural network exist uniquely, and at the same time, we also obtain its global exponential stability. Different from previous studies, we consider neural network systems in the complex number domain. Thus, the conclusions obtained have broader applicability. Finally, we present a numerical example to verify the validity of the result.